Cost Estimation
Problem
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Our ability to realistically plan and schedule
projects depends on our ability to estimate
project costs and development efforts
In order to come up with a reliable cost
estimate, we need to have a firm grasp on the
requirements, as well as our approach to
meeting them
Typically costs need to be estimated before
these are fully understood
Estimating uncertainty
Boehm
1981
What are project
costs?
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For most software projects, costs are:
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Hardware Costs
Travel & Training costs
Effort costs
What are effort costs?
• Effort costs typically largest of the 3 types
of costs, and the most difficult to estimate.
• Effort costs include:
– Developer hours
– Heating, power, space
– Support staff; accountants, administrators, cleaners,
management
– Networking and communication infrastructure
– Central facilities such as rec room & library
– Social security and employee benefits
Effort cost estimation - Overhead
• Everything other than salaries
• OSU example:
– 45% for benefits
– 46% for “indirect” costs (space, infrastructure etc)
calculated on top of everything else
$1,000 +benefits ($450) + infrastructure ($667)
= $2,117
Software cost estimation –
Boehm (1981)
• Algorithmic cost modeling
– Base estimate on project size (lines of code)
• Expert judgment
– Ask others
• Estimation by analogy
– Cost based on experience with similar projects
• Parkinson’s Law
– Project time will expand to fill time available
• Pricing to win
– Cost will be whatever customer is willing to pay
• Top-down estimation
– Estimation based on function/object points
• Bottom-up estimation
– Estimation based on components
Aggravating & mitigating factors
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Market opportunity
Uncertainty/risks
Contractual terms
Requirements volatility
Financial health
Opportunity costs
Cost drivers
• Software reliability
• Size of application
database
• Complexity
• Analyst capability
• Software engineering
capability
• Applications experience
• Virtual machine
experience
• Programming language
expertise
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Performance requirements
Memory constraints
Volatility of virtual machine
Environment
Turnaround time
Use of software tools
Application of software
engineering methods
• Required development
schedule
Productivity metrics
• Lines of code
– Simple, but not very meaningful metric
– Easy to pad, affected by prog language
– How to count revisions/debugging etc?
• Function points
– Amount of useful code produced
(goals/requirements met)
– Less volatile, more meaningful, not perfect
Function points
Function points are computed by first calculating an
unadjusted function point count (UFC). Counts are made
for the following categories (Fenton, 1997):
– External inputs – those items provided by the user that describe
distinct application-oriented data (such as file names and menu
selections)
– External outputs – those items provided to the user that
generate distinct application-oriented data (such as reports and
messages, rather than the individual components of these)
– External inquiries – interactive inputs requiring a response
– External files – machine-readable interfaces to other systems
– Internal files – logical master files in the system
Each of these is then assessed for complexity and given a
weighting from 3 (for simple external inputs) to 15 (for
complex internal files).
Unadjusted Function Point Count
(UFC)
Weighting Factor
Item
Simple
Average
Complex
External inputs
3
4
6
External outputs
4
5
7
External inquiries 3
4
6
External files
7
10
15
Internal files
5
7
10
Each count is multiplied by its corresponding complexity
weight and the results are summed to provide the UFC
Object points
Similar to function points (used to estimate
projects based heavily on reuse, scripting
and adaptation of existing tools)
• Number of screens (simple x1, complex x2, difficult
x3)
• Number of reports (simple x2, complex x5, difficult x8)
• Number of custom modules written in languages like
Java/C x10
Function points -> Lines of code
200-300 LOC/Function
point in assembly
Multiplication factor by
language
Programmer
productivity?
COCOMO II Model
• Supports spiral model of development
• Supports component composition, reuse, customization
• 4 sub-models:
– Application composition model – assumes system written with
components, used for prototypes, development using scripts,
db’s etc (object points)
– Early design model – After requirements, used during early
stages of design (function points)
– Reuse model – Integrating and adapting reusable components
(LOC)
– Post architecture model – More accurate method, once
architecture has been designed (LOC)
Application composition model
Used primarily to estimate cost of
prototyping efforts
PM = (Application points x(1-%reuse/100)/ productivity
Productivity estimates from 4-50 object
points/month, depending on experience
and the availability/maturity of tools
Early Design Model
Used once requirements are agreed to get
going on an architectural design
PM=2.94 x Size^B x M
B=1.05-1.20
M=Proj characteristics
Reuse model
• PM = (LOC needing to be adjusted X
% auto-generated)/productivity
Productivity ~ 2,400 LOC/Month
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Post-Architectural
Model
Organic projects - relatively small, simple projects with
small teams and good application experience to less than
rigid requirements. (A=2.4, B=1.05)
Semi-detached projects - intermediate (in size and
complexity) projects with mixed experience teams and a
mix of requirements. (A=3.0, B=1.12)
Embedded projects - software projects that must be
developed within a set of tight hardware, software, and
operational constraints. (A=3.6, B=1.20)
PM=A x Size^B x M